A majority of uninfected adults show pre-existing antibodies against SARS-CoV-2
insight.jci.org
insight.jci.org
> Now, you can still make an argument that the T cell component of immunity might provide some protection after a previous coronavirus infection. The current study didn’t address this directly, but after these results, it’s at least less likely that that’s happening. The authors make a note of this, and also note that pre-existing mucosal antibodies might exert a protective effect (which this study didn’t examine, either). But prior circulating human coronavirus antibodies, even ones that can bind to the current one – those it looks like we can rule out. Which is too bad.
From: https://blogs.sciencemag.org/pipeline/archives/2021/02/10/do...
The title study here is nothing new, we know there's cross reactive antibodies to other coronaviruses, they're not neutralizing, the hospitalization/death rates are the same so they don't confer any protection.
Nobody had any pre-existing immunity to this virus before it erupted last year (and no, the virus or variants of it were not traveling the globe months or years earlier).
And super intriguing!
Viruses don't spring from nowhere, or jump from caves 1000km away to an urban population that just happens to have a lab studying them. I just find the coincidence here too great.
My money is on still on someone associated with the lab became the vector where what they were working on gained function from some other highly spreadable coronavirus. Only takes one protocol breach for a PPE failure, and these labs worldwide seem to have lapses all the time.
They need to find a sample of this mystery virus that was circulating beforehand and see if it had the novel ACE2 receptor binding that the bat virus most like SARS-Cov-2 lacked - maybe then they can put the hypothesis that the lab was involved to rest.
This current we don't really know how it happened is bullshit.
The summer 2019/20 spike in hospitalised pneumonia cases in the southern hemisphere that were a non-flu virus is another data point out there - someone just needs to put them all together.
https://threadreaderapp.com/thread/1249414291297464321.html
https://www.nejm.org/doi/full/10.1056/NEJMc2008646
The viruses going around 19/20 winter in WA included all kinds of non-flu viruses. The rapid flu test also suffers from the same 50% false negative rate that the rapid COVID test suffers from.
I would normally kind of shit all over anyone outside of China claiming to have caught the virus in 2019, but you tick off the two boxes which are complete and total loss of smell and contact tracing to someone actually back in China. Presumably you didn't pass it on to anyone or it otherwise died out and never found a superspreader (the majority of chains of infections of SARS-CoV-2 actually die out due to the way it transmits mostly by superspreading and it can take 4+ "seeds" on average before epidemic spread kicks off in an area).
> The findings of this study indicate that that it is possible the virus that causes COVID-19 may have been present in California, Oregon, and Washington as early as Dec. 13-16, 2019, and in Connecticut, Iowa, Massachusetts, Michigan, Rhode Island, and Wisconsin as early as Dec. 30, 2019 - Jan. 17, 2020.
> In order to better characterize the specimens that were reactive on the pan-Ig ELISA containing whole SARS-CoV-2 spike protein as the capture antigen, and distinguish these from cross-reactivity to common coronaviruses, additional, more specific SARS-CoV-2 testing was performed. The S1 subunit has been reported to be a more specific antigen for SARS-CoV-2 serologic diagnosis than the whole S protein [23]. Furthermore, in recent studies, sera from patients with confirmed human coronavirus infection only contained SARS-CoV-2 S protein–specific IgG antibodies and did not contain IgM or IgA antibodies; neutralizing activity in these sera was found to target only the S2 portion of the spike protein [23, 24]. Therefore, the presence of IgM or IgA antibodies and S1-specific binding activity may distinguish antibodies to SARS-CoV-2 from antibodies to human common coronaviruses [23, 24]. In the present study, 84 of 90 (>93%) reactive sera had neutralizing activity against SARS-CoV-2 virus, 39 (44.3%) had both IgG and IgM SARS-CoV-2 S protein–specific antibodies, 2 (2.2%) sera had surrogate neutralization activities, and 1 of 90 (1.1%) had SARS-CoV-2 S1-specific Ig. Collectively, these data suggest that at least some of the reactive blood donor sera could be due to prior SARS-CoV-2 infection. One serum sample, collected on 10 January 2020 in Connecticut, demonstrated a neutralization titer of 320, a signal-to-threshold ratio of 6.75, and 70% inhibition activity by surrogate neutralization activity, but was Ortho S1 nonreactive. These data indicate that this donation was likely from an individual with a past or active SARS-CoV-2 infection.
They found maybe two good signals for SARS-CoV-2 infection, with only one in Jan 2020 that really passes the test for definitively being SARS-CoV-2 infection. The neutralizing titers were in the total absence of IgG/IgM SARS-CoV-2 S-protein specific antibodies, which can be cross reactivity to antibodies against other coronaviruses. The fact that they were neutralizing against SARS-CoV-2 though in vitro doesn't necessarily confer actual protection as was seen in the study that Derek Lowe cites.
That study is still consistent with not knowing of any SARS-CoV-2 infections in the USA in 2019 and there being nothing possible other than cryptic spread.
And the poorer/denser the country, even more congregation in the fewer climate controlled spaces there are.
It is unclear whether this antibody reactivity may confer clinical benefits, for instance, modulating the severity of a SARS-CoV-2 infection.
I think quantifying any protective effect is gonna be pretty difficult.
The trouble is that the article has a clickbait title: "A majority of uninfected adults show pre-existing antibody reactivity against SARS-CoV-2". Which may get translated into "We already have herd immunity" by some television pundit shortly.
What data is there that indicates this is the case?
I'm Brazilian born and raised, and even though have been out for about 7 years most of my friends and family are still there.
The fact that pretty much everybody I know over there knows at least a handful of people who have died of COVID-19 and hell knows how many that have had it is not "how the media reports it".
The struggle is real, the situation is pretty dire over there.
Young healthy people have never been at risk.
A more accurate way to phrase this is that young non-overweight people are at far less risk than young obese people. It's not true that young healthy people are at no risk.
From https://jamanetwork.com/journals/jamainternalmedicine/fullar...:
Among 780969 adults discharged between April 1, 2020, and June 30, 2020, 63103 (8.1%) had the ICD-10 code for COVID-19, of whom 3222 (5%) were nonpregnant young adults (age 18-34 years) admitted to 419 US hospitals. The mean (SD) age of this population was 28.3 (4.4) years; 1849 (57.6%) were men and 1838 (57.0%) were Black or Hispanic. Overall, 1187 (36.8%) had obesity, 789 (24.5%) morbid obesity, 588 (18.2%) diabetes, and 519 (16.1%) hypertension (Table).
During hospitalization, 684 patients (21%) required intensive care, 331 (10%) required mechanical ventilation, and 88 (2.7%) died. Vasopressors or inotropes were used for 217 patients (7%), central venous catheters for 283 (9%), and arterial catheters for 192 (6%). The median length of stay was 4 days (interquartile range, 2-7 days). Among those who survived hospitalization, 99 (3%) were discharged to a postacute care facility.
Morbid obesity (adjusted odds ratio [OR], 2.30; 95% CI, 1.77-2.98; vs no obesity; P < .001) and hypertension (adjusted OR, 2.36; 95% CI, 1.79-3.12; P < .001) were common and in addition to male sex (adjusted OR, 1.53; 95% CI, 1.20-1.95; P = .001) were associated with greater risk of death or mechanical ventilation. Odds of death or mechanical ventilation did not vary significantly with race and ethnicity. Morbid obesity was present in 140 patients (41%) who died or required ventilation.
So, 3222 / 780969 = 0.4% of the examined population had admission to a hospital with "Covid" on their forms. Of these, 343 died (0.04% of examined population; Table 1).
Obesity, hypertension and diabetes were strongly correlated with death in this population.
That's not "no risk", but it's consistent with the OP's comment: the risk for young people is quite low, and is concentrated amongst the obese (and diseases related to obesity).
Just for the obvious extreme example, if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
It tells you what to expect if you're a doctor working with hospitalized patients, or if you run a hospital.
This is why they did the study.
> if I say 0.01% of total hospitalizations are young people with ebola, that doesn't let you conclude anything about whether catching ebola is "quite low risk" for that group.
1) that's not what this study calculated. You still don't understand it.
The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
They took a population of young people hospitalized for Covid, removed the pregnancies, and looked at what happened to the rest. That's it. It doesn't tell you anything about "catching Covid". It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
I know that.
> 2) They weren't trying to say anything about catching the virus. I understand that you really want to use this paper to make the claim, but it's just not relevant.
I know that, and I wasn't talking about catching, I was talking about the risk of death if you catch it.
> The equivalent study would be "of young people hospitalized with ebola, what percentage of them die?" (and BTW, the answer would be: "a huge percentage of them"...unlike Covid.)
> It does tell you that if you're young and not obese, not diabetic and don't have heart disease, you are overwhelmingly likely not to die from it.
I'm not sure what your definition of "overwhelming" is so I'll put it this way:
Of young people hospitalized, the percentage chance of death is still pretty high. The numbers you quoted were 10 percent! I'm pretty sure you quoted wrong and the real number is 3 percent, but that's still a very real chance of death that you should try very strongly to avoid.
The original quote was "Young healthy people have never been at risk."
Your amended version was "the risk is quite small indeed".
Neither of those fits a 3 percent death rate, even after taking into account the risk factors and focusing on patients without them. That chance of death is something that might be acceptable once or twice in your entire life after great consideration.
The only way to get a "small" risk here is to factor in a sufficient number of people that catch it but never end up in the hospital at all (if there are enough of them). Going purely by the hospital numbers it's not something to brush off at all.
I didn't bother to explain that part because I didn't think you were actually suggesting that 343 out of 3222 is quite low risk! I assumed you were talking about a different number.
But a nontrivial percentage of young people hospitalized for COVID are not obese, and some otherwise healthy young people have died.
So the claim is false. "Much less risk" is not "no risk."
If you want to attack someone (again: not me) for saying "there's no risk to young people unless they're obese" -- which is essentially what the OP said -- then that's your prerogative, but I have better places to grind axes.
I think it's important to make it clear that the risk is quite small indeed, and let people make up their own minds. That's different than implying that a "non-zero risk" is somehow meaningful to a young person.
We do not have a definition for "long covid", let alone enough information to make such a claim.
At best, this is blatant speculation, at worst, it's completely false. The best data for long-term sequelae of Covid indicate that it correlates with disease severity, which itself correlates (strongly) with age.
That said, the news media has been shameless about misinterpreting data consistently in order to promote fear. It's a real problem.
The idea that a young person is safe is convenient for young people, but irrelevant. We never seemed to communicate to a segment of the population that we are trying to keep them from spreading it, as well as keeping them from catching it.
I understand that without symptoms like coughing or sneezing, the vector for spreading would be relatively limited, but I have to imagine it's still possible (even commonplace) for healthy individuals to effectively spread bacteria/viruses (even harmless ones).
If it is possible, what are the chances of that happening unintentionally? Would it be ethical to engineer a vaccine to intentionally do that?
I'm not trying to imply that's what's happening now - but I am curious.
Artificially creating such a thing has been discussed, but I don't think anyone's ready to go there for ethical reasons. What if they screw it up?
Also, you still need _some_ symptoms to get people to sneeze the "vaccine" to their neighbors. It's a very fine line to tread.
It will also be more challenging going forward to do these kinds of studies because of the ethics. It will be hard to ethically justify keeping an arm of a trial unvaccinated as a placebo in the face of a very serious and very deadly virus which we have known good vaccines. There are some interesting things like crossover trials that apparently more of the current in research vaccines are trying.
The mRNA COVID vaccines are not; with those, the vaccine material is mRNA that your body codes into a protein recognizable to the immune system. The mRNA is both unstable (so it doesn't last long inside the body) and not capable of contagious transmission
There is open research, such as https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5777272/, as to whether making intentionally transmissible vaccines is feasible (or even a good idea)
If a vaccine used a virus that was both live and contagious but somehow safe, its not impossible; of course, there’d also be a risk of it mutating to become unsafe.
The actual vaccines for protection against COVID-19 that I know of don’t use a delivery mechanism where that is possible; that’s certainly not something, e.g., a mRNA vaccine could do.
This number seems low. I think the title is poorly worded, to me it concludes more of that healthcare workers in Canada developed antibodies before being diagnosed with COVID-19
If you are exposed to 1000 versus 100,000, does one lead to an infection while the other indices some exposure response?
The thing the study establishes is that most adults have antibodies that will react to some parts of the pandemic virus. And then that's it. They didn't establish whether it was protective or not or anything like that.
Could this explain why many people have mild cases but some have severe cases? I’d be curious to find out how effective the cross-reactive antibodies are compared to ones produced by a vaccine.
https://www.iflscience.com/health-and-medicine/prior-exposur...
Although I don't usually seek out this topic in this community, I find these discussions here helpful from time to time.
edit: Not implying SAR COV-2 is "a cold". I'm implying it's a coronavirus also like the common cold, hence an antibody study would have to be careful to select for the right one.
The antibody tests are designed with high specificity for particular antibodies, this study went out of their way to look for any reactivity.
The emergency use authorizations allowed anyone who plausibly had a test to market it, even if it had not been independently validated in any way by anyone. Many folks just bought what they could find, even if it didn’t have an emergency use authorization.
Combined with porous borders, e-commerce and the internet, lack of consequences for someone in China to ship junk here? We got buried in (at best) untested junk, and often outright scams.
This has resulted in a rather predictable disaster when it comes to data and awareness - very few of the tests are being cross referenced to other data sources or tested against an independently verified data source, and even fewer (if any) are being evaluated by a independent party. The vast majority of tests in April have since been removed from authorization because they don’t work, don’t work well enough, etc. You can read a very nice paper from the FDA here summarizing it. [https://www.nejm.org/doi/full/10.1056/NEJMp2033687]
As far as I am aware, there is still no clear picture on which tests have actually been validated, by whom, and to what extent against what data set. Will they pick up variants, and if so which ones? With what accuracy? What are common field errors (collection problems, etc) that can lead to problems? What about manufacturing variance and supply chain issues?
You've raised the bar a long ways from except in a very small number of cases not actually validated in the field to perform that way to a comprehensive analysis of all tests that have even maybe been available.
Of course, the 'very small number of cases' makes it impossible to argue without doing a comprehensive study, but it's clear enough that the widely used commercial tests were developed with the idea that they should minimize false positives and tested against pre-Covid serum.
Do you have any data on which tests are widely used? (As in by number of tests done?)
I’m hoping it’s shifted the way you’re saying, but as of November there were more BS ones than legit ones, and it was hard to find a real validated test. None of the folks I knew getting antibody tests were able to find any of the validated ones.
That validated tests are good is great if they are being used, or used widely. Because in November the ones being used widely were still junk, which was my point.
If you have, per your study, 3 tests that are validated - are they used in the field for these studies? If so, objection withdrawn for current studies using them.
If they are studies based on the older, unvalidated, and often junk tests - then that point still stands.
it's not the virus but rather our bodies that are so mysterious. the virus is relatively simple in comparison (which is different from saying we know everything about it, since we obviously don't).
To get somewhat useful data, you’d probably need to do that for at least a couple thousand folks (10k each arm would be my guess), so you’re looking at what, 5 million total in the study, 2.5 million exposed? Based on the best data we had at the time (assumed 3.5% fatality rate I believe?), that would have been 87k fatalities out of that group. [https://www.who.int/bulletin/volumes/99/1/20-265892/en/ ], Currently seems like estimates are around 1-2% which would drop it to only 25-50k [https://www.nature.com/articles/s41392-021-00527-1].
For many very, very good reasons that isn’t how we roll right now though, and we do have good technology for solving this either. Star Trek style ‘simulate’ mode is a looong way away in this space.
Looking forward to it hopefully getting better soon though - a lot of money going into getting this figured out.
in general, we have trouble modulating our attention and resource allocation around unique events like this, and it behooves us to zoom out and put it in the proper context.
From https://www.reuters.com/article/us-health-coronavirus-scienc...:
Along with inducing antibodies for immediate defense, mRNA vaccines against COVID-19 also stimulate the lymph nodes to generate immune cells that provide protection over the long term, a new study confirms. The early wave of antibodies are generated by B cells called plasmablasts. In healthy volunteers, blood tests showed that two doses of the Pfizer/BioNTech vaccine induced "a strong plasmablast response," said coauthor Ali Ellebedy of Washington University School of Medicine in St. Louis. The immune cells that will produce antibodies upon exposure to the virus in years to come - called memory B cells - are generated by germinal center B cells found only in lymph nodes near vaccine injection sites, his team explained in a paper currently undergoing peer review for possible publication in a Nature journal. In repeated biopsies of volunteers' lymph nodes, "we saw a robust germinal center response," Ellebedy said. The responses lasted at least seven weeks, "with no sign of cooling down anytime soon," he added. "While we do not have long-term samples yet, it is safe to assume given the magnitude and persistence of the germinal center reaction that those individuals will develop a durable immune response" to mRNA vaccines. Moderna Inc's vaccine also uses mRNA technology.
this list is not comprehensive.
From what I can find online, there's a correlation, but it's pretty light on details about how strong it is.
> Sense of "indisposition involving catarrhal inflammation of the mucous membranes of the nose or throat" is from 1530s, so called because the symptoms resemble those of exposure to cold; compare cold (n.) in earlier senses "indisposition or disease caused by excessive exposure to cold" (early 14c.), "chills of intermittent fever" (late 14c.).
Put less technical: shivering, runny nose, etc, are symptoms of both the common cold and being cold.
It seems it's best to think of "cold" and "flu" as totally informal terms with a wide range of possible meanings. I've had Actual Real Influenza twice and both times it knocked me on my ass for a week, lost weight, etc. yet I hear people saying "I have the flu" when they have mild symptoms and only miss a single day of work. Hard to take such a wide range medically seriously.
They could have had influezna with mild symptoms. Two different people can have the same influenza virus enter their body and experience different effects. Anywhere from no symptoms at all to death.
In this case, 77% of participants were in the medical profession and were evaluated between May and June 2020. I suspect they came in contact with SAR COV-2 and didn't even realize it (body fought it off).
What this study is really suggesting is that your body either (a) has an immune response from previous contact (likely due to similarity with regular corona viruses) or (b) lots of people show no symptoms (we know this) and that they obtain an immune response from it.
In either case, the SAR COV-2 is likely far-less dangerous in the sense that more people have it and there are less deaths per infection OR many of us have a natural immune response (more than previously suspected).
It is unclear whether this antibody reactivity may confer clinical benefits, for instance, modulating the severity of a SARS-CoV-2 infection.
Not really. Mortality rate is number of deaths / number of infections.
We roughly know the total number of deaths. We have no idea what the total number of infections has been.
We should continue to make decisions based on the pretend mortality rate and ignore the true one?
Of course we "want to know it."
However the “pretend mortality rate” you refer to is not a thing. It is 1-3% in people who test positive, which correlates pretty strongly with people who have the disease. Think about it this way: the yearly flu in 2018-2019 had a mortality rate of 1.3-48.7% according to the CDC. The denominator in that was 61,000 or so cases. If you found out that 100,000 additional people were exposed to the flu but had no symptoms and by any definition had no flu illness would that change your outlook on whether the flu vaccine or hand washing is worth it?
Or another example: there is surgery which has a mortality rate of 15% due to post surgery infection. Not everybody needs the surgery, only 100 people per year do. Does that mean the rate of mortality here is fake because the denominator should be 7.5 billion? Or should we only count the people who get the disease that necessitates the surgery?
Yes, of course my outlook would change. Not on the binary scale--i wouldn't suddenly think it's not worth it to wash hands-- but I would want to know when deciding on measures.
The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
If some people get the virus and have no symptoms, that's an incredibly important piece of the puzzle when deciding how to proceed.
Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
This study does not tell you that these people had COVID. That's the point: we don't know what this means. All we know, is that we need to study this further.
> The mortality rate is a specific figure, it's not whatever figure makes your reaction most appropriate.
From Wikipedia: "Mortality rate, or death rate, is a measure of the number of deaths (in general, or due to a specific cause) in a particular population, scaled to the size of that population, per unit of time." What is the "particular population" here is in question. I argue that "people who had the SARS-CoV-2 disease" are the relevant population. That is, people who had symptoms or tested positive after an exposure. This study does not change this because it shows no source of the antibodies: if I inject my COVID-19 antibodies into your arm, it does not mean that you had the disease and therefore should not be counted in the mortality rate, does it? How those antibodies got there is a question yet to be answered but the possible answers range from "those people got a mild case and didn't notice" to "those people developed low level antibodies due to incidental contact with COVID-19" without getting the the illness. Their immune system is not trained well enough to fight off a higher viral load."
> Using your exaggerated examples, what if 99% of the population didn't suffer any adverse effects? Wouldn't you reevaluate the current response in light of that?
Yes and no. First, this study does not tell me anything regarding suffering adverse effects. But if a future study did, I think the 3 million people that have died so far would have wanted us to take more precautions, not less, just because we, the living, won the antibody lottery. At the end of the day this is a highly infectious + somewhat deadly disease that adds up to one deadly pandemic. If your point is that only another few million will die if we let it run rampant vs all of humanity, I don't disagree with you but urge you to examine what it means to let millions of people die in this case.
well it possibly changes the calculus of how many people could potentially be a carrier of the virus. if that many people had the disease enough to have some antibodies even with all the extreme measures put into place it is possible this virus is even more contagious than we thought it could be. i don't know and i feel like we won't know because the study of transmission is woefully hard to do. going into this we didn't even know specifically how the flu was transmitted other than hand waving ways(maybe on the surface, maybe aerosols, maybe particles). our research has improved but it's still not great.
So there's the mortality rate for the overall population (what GP is referencing) vs mortality rate among people who've had COVID (what I believe you're referencing). Both are valid and useful in different circumstances: "How likely am I to die if I get COVID" changes as we discover a glut of asymptomatic cases, but "What % of the population will die of this disease?" stays the same
Ref: https://www.merriam-webster.com/dictionary/mortality%20rate
https://www.merriam-webster.com/dictionary/case%20fatality%2...
That doesn’t sound right — you can’t know the population death rate definitely without knowing the infection rate;
If no one gets the disease in your sample population of 100, your death rate says 0. If 1 person is infected and 1 dies, your population death rate says 1%. If 80 are infected, and 10 dies, your population death says 10%.
The “correct” number should be stable, but the population death rate should be changing as the disease spreads, approaching the correct number (but this is also true of liklihood of dying to COVID)
Your population death rate would only be static if your sample population is 100% infected, which is the same as “How likely am I to die if I get COVID”
As another example: lots of people have the tuberculosis infection which lies dormant in their lungs. TB infection is distinct from TB disease which is where you get symptoms. The former is only dangerous in that it can develop into the latter. The latter can kill you. How should you look at these numbers? Is it worthwhile to drop the number of people with TB disease and just divide deaths by TB infections or is it more informative to derive mortality as deaths / TB diseases while also using TB infections and the conversion rate from those to TB disease to calculate risk and transmissibility? I argue the latter is much more relevant to decision making.
Strikes me as similar to those who predict x% returns on their s&p index funds based on past stock market performance.
The future is always unknown.
We know deaths / symptomatic infections really well due to the large numbers involved.
1. What percentage of these people can catch COVID.
2. How likely they are to infect someone else if they do.
For some reason, communities around the world keep getting second, third, fourth, and fifth waves of infections, and viral variants keep evolving, despite the proliferations of studies like this.
It's like measuring the level of humidity at ground level, and using that to conclude that it's raining. Yes, there's a correlation. No, that's not a reliable way to measure rainfall. A reliable way to measure rainfall is putting a bucket out.
The fact that communities open up -> communities get another wave of COVID keeps playing out over and over again leads me to believe that neither #1 or #2 are likely to be favourable to us.